Krawczak, Maciej.
Multilayer Neural Networks A Generalized Net Perspective / [electronic resource] : by Maciej Krawczak. - XII, 182 p. online resource. - Studies in Computational Intelligence, 478 1860-949X ; . - Studies in Computational Intelligence, 478 .
Introduction to Multilayer Neural Networks -- Basics of Generalized Nets -- Simulation Process of Neural Networks -- Learning from Examples -- Learning as a Control Process -- Parameterisation of Learning -- Adjoint Neural Networks.
The primary purpose of this book is to show that a multilayer neural network can be considered as a multistage system, and then that the learning of this class of neural networks can be treated as a special sort of the optimal control problem. In this way, the optimal control problem methodology, like dynamic programming, with modifications, can yield a new class of learning algorithms for multilayer neural networks. Another purpose of this book is to show that the generalized net theory can be successfully used as a new description of multilayer neural networks. Several generalized net descriptions of neural networks functioning processes are considered, namely: the simulation process of networks, a system of neural networks and the learning algorithms developed in this book. The generalized net approach to modelling of real systems may be used successfully for the description of a variety of technological and intellectual problems, it can be used not only for representing the parallel functioning of homogenous objects, but also for modelling non-homogenous systems, for example systems which consist of a different kind of subsystems. The use of the generalized nets methodology shows a new way to describe functioning of discrete dynamic systems. .
9783319002484
10.1007/978-3-319-00248-4 doi
Engineering.
Artificial intelligence.
Computational intelligence.
Control engineering.
Engineering.
Computational Intelligence.
Artificial Intelligence (incl. Robotics).
Control.
Q342
006.3
Multilayer Neural Networks A Generalized Net Perspective / [electronic resource] : by Maciej Krawczak. - XII, 182 p. online resource. - Studies in Computational Intelligence, 478 1860-949X ; . - Studies in Computational Intelligence, 478 .
Introduction to Multilayer Neural Networks -- Basics of Generalized Nets -- Simulation Process of Neural Networks -- Learning from Examples -- Learning as a Control Process -- Parameterisation of Learning -- Adjoint Neural Networks.
The primary purpose of this book is to show that a multilayer neural network can be considered as a multistage system, and then that the learning of this class of neural networks can be treated as a special sort of the optimal control problem. In this way, the optimal control problem methodology, like dynamic programming, with modifications, can yield a new class of learning algorithms for multilayer neural networks. Another purpose of this book is to show that the generalized net theory can be successfully used as a new description of multilayer neural networks. Several generalized net descriptions of neural networks functioning processes are considered, namely: the simulation process of networks, a system of neural networks and the learning algorithms developed in this book. The generalized net approach to modelling of real systems may be used successfully for the description of a variety of technological and intellectual problems, it can be used not only for representing the parallel functioning of homogenous objects, but also for modelling non-homogenous systems, for example systems which consist of a different kind of subsystems. The use of the generalized nets methodology shows a new way to describe functioning of discrete dynamic systems. .
9783319002484
10.1007/978-3-319-00248-4 doi
Engineering.
Artificial intelligence.
Computational intelligence.
Control engineering.
Engineering.
Computational Intelligence.
Artificial Intelligence (incl. Robotics).
Control.
Q342
006.3